{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# BranchTupleOutput"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import tvm\n",
    "from tvm import relax\n",
    "from tvm.relax.backend.cuda.cublas import partition_for_cublas\n",
    "from tvm.relax.backend.cuda.cutlass import partition_for_cutlass\n",
    "from tvm.relax.dpl.pattern import (\n",
    "    is_op,\n",
    "    is_tuple_get_item,\n",
    "    make_fused_bias_activation_pattern,\n",
    "    wildcard,\n",
    ")\n",
    "from tvm.relax.transform import PatternCheckContext\n",
    "from tvm.script import ir as I\n",
    "from tvm.script import relax as R\n",
    "from tvm.script import tir as T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv2d_pat = make_fused_bias_activation_pattern(\"relax.nn.conv2d\", activation=None)\n",
    "conv2d_relu_pat = make_fused_bias_activation_pattern(\"relax.nn.conv2d\", activation=\"relax.nn.relu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "@tvm.script.ir_module\n",
    "class BranchTupleOutput:\n",
    "    @R.function\n",
    "    def main(\n",
    "        data: R.Tensor((1, 64, 56, 56), \"float32\"),\n",
    "        weight: R.Tensor((64, 64, 3, 3), \"float32\"),\n",
    "    ):\n",
    "        with R.dataflow():\n",
    "            conv1 = R.nn.conv2d(data, weight)\n",
    "            relu1 = R.nn.relu(conv1)\n",
    "            gelu1 = R.nn.gelu(relu1)\n",
    "            gelu2 = R.nn.gelu(conv1)\n",
    "            out = relax.op.add(gelu1, gelu2)\n",
    "            R.output(out)\n",
    "\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"highlight\" style=\"background: \"><pre style=\"line-height: 125%;\"><span></span><span style=\"color: #007979; font-style: italic\"># from tvm.script import ir as I</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "\n",
       "<span style=\"color: #AA22FF\">@I</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>ir_module\n",
       "<span style=\"color: #008000; font-weight: bold\">class</span> <span style=\"color: #0000FF; font-weight: bold\">Module</span>:\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">main</span>(data: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), weight: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>):\n",
       "        <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "            conv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(data, weight, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            relu1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(conv1)\n",
       "            gelu1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>gelu(relu1)\n",
       "            gelu2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>gelu(conv1)\n",
       "            out: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(gelu1, gelu2)\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(out)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> out\n",
       "</pre></div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "BranchTupleOutput.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "patterns =  [(\"dnnl.conv2d_relu\", conv2d_relu_pat),]\n",
    "bind_constants = True\n",
    "annotate_codegen = True\n",
    "partitioned = relax.transform.FuseOpsByPattern(patterns, bind_constants, annotate_codegen)(BranchTupleOutput)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"highlight\" style=\"background: \"><pre style=\"line-height: 125%;\"><span></span><span style=\"color: #007979; font-style: italic\"># from tvm.script import ir as I</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "\n",
       "<span style=\"color: #AA22FF\">@I</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>ir_module\n",
       "<span style=\"color: #008000; font-weight: bold\">class</span> <span style=\"color: #0000FF; font-weight: bold\">Module</span>:\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">fused_relax_nn_conv2d_relax_nn_relu_dnnl</span>(data: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), weight: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        R<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;Codegen&quot;</span>: <span style=\"color: #BA2121\">&quot;dnnl&quot;</span>})\n",
       "        <span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "        \n",
       "        <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "        <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">local_func</span>(data_1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), weight_1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;Composite&quot;</span>: <span style=\"color: #BA2121\">&quot;dnnl.conv2d_relu&quot;</span>})\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "                gv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(data_1, weight_1, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "                gv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(gv)\n",
       "                R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(gv, gv1)\n",
       "            <span style=\"color: #008000; font-weight: bold\">return</span> (gv1, gv)\n",
       "\n",
       "        output: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> local_func(data, weight)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> output\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">main</span>(data: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), weight: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>):\n",
       "        cls <span style=\"color: #AA22FF; font-weight: bold\">=</span> Module\n",
       "        <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "            lv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>fused_relax_nn_conv2d_relax_nn_relu_dnnl(data, weight)\n",
       "            lv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv[<span style=\"color: #008000\">1</span>]\n",
       "            lv2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv[<span style=\"color: #008000\">0</span>]\n",
       "            gelu1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>gelu(lv2)\n",
       "            gelu2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>gelu(lv1)\n",
       "            out: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">54</span>, <span style=\"color: #008000\">54</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(gelu1, gelu2)\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(out)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> out\n",
       "</pre></div>\n"
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